Risk-Sensitive Reinforcement Learning
Author:
Publisher
Springer US
Link
http://link.springer.com/content/pdf/10.1007/978-1-4419-1428-6_1881
Reference6 articles.
1. Basu, B., & Borkar, V. S. (2008). A learning algorithm for risk-sensitive cost. Mathematics of Operations Research, 33(4), 880–898.
2. Coraluppi, S. P., & Marcus, S. I. (1999). Risk-sensitive, minimax and mixed riskneutral/minimax control of markov decision processes. In W. M. McEarney, G. G. Yin, & Q. Zhang (Eds.), Stochastic analysis, control, optimization and applications (pp. 21–40). Boston: Birkhäuser.
3. Geibel, P., & Wysotzki, F. (2005). Risk-sensitive learning applied to control under constraints. Journal of Artificial Intelligence Research, 24, 81–108.
4. Heger, M. (1994, July 10–13). Consideration of risk in reinforcement learning. In W W. Cohen, & H. Hirsh (Eds.), Machine learning, Proceedings of the eleventh international conference (pp. 105–111). Rutgers University, New Brunswick, NJ: Morgan Kaufmann.
5. Mihatsch, O., & Neuneier, R. (2002). Risk-sensitive reinforcement learning. Machine Learning, 49(2–3), 267–290.
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